Molecular Correlates of Metastasis by Systematic Pan-Cancer Analysis Across The Cancer Genome Atlas

Identification and characterization of TM4SF1+ tumor self-seeded cells

Tumor self-seeding is a process whereby circulating tumor cells (CTCs) recolonize the primary tumor, which promotes tumor growth, angiogenesis, and invasion. However, the detailed nature and functions of tumor self-seeded cells (TSCs) have not been well defined due to challenges in tracking and isolating TSCs. Here, we report an accurate animal model using photoconvertible tagging to recapitulate the spontaneous process of tumor self-seeding and identify TSCs as a subpopulation of primary tumor cells with enhanced invasiveness and survival. We demonstrate transmembrane-4-L-six-family-1 (TM4SF1) as a marker of TSCs, which promotes migration, invasion, and anchorage-independent survival in cancer cells. By analyzing single-cell RNA sequencing datasets, we identify a potential TSC population with a metastatic profile in patients with cancer, which is detectable in early-stage disease and expands during cancer progression. In summary, we establish a framework to study TSCs and identify emerging cell targets with diagnostic, prognostic, or therapeutic potential in cancers.

An essential gene signature of breast cancer metastasis reveals targetable pathways

BACKGROUND

The differential gene expression profile of metastatic versus primary breast tumors represents an avenue for discovering new or underappreciated pathways underscoring processes of metastasis. However, as tumor biopsy samples are a mixture of cancer and non-cancer cells, most differentially expressed genes in metastases would represent confounders involving sample biopsy site rather than cancer cell biology.

METHODS

By paired analysis, we defined a top set of differentially expressed genes in breast cancer metastasis versus primary tumors using an RNA-sequencing dataset of 152 patients from The Breast International Group Aiming to Understand the Molecular Aberrations dataset (BIG-AURORA). To filter the genes higher in metastasis for genes essential for breast cancer proliferation, we incorporated CRISPR-based data from breast cancer cell lines.

RESULTS

A significant fraction of genes with higher expression in metastasis versus paired primary were essential by CRISPR. These 264 genes represented an essential signature of breast cancer metastasis. In contrast, nonessential metastasis genes largely involved tumor biopsy site. The essential signature predicted breast cancer patient outcome based on primary tumor expression patterns. Pathways underlying the essential signature included proteasome degradation, the electron transport chain, oxidative phosphorylation, and cancer metabolic reprogramming. Transcription factors MYC, MAX, HDAC3, and HCFC1 each bound significant fractions of essential genes.

CONCLUSIONS

Associations involving the essential gene signature of breast cancer metastasis indicate true biological changes intrinsic to cancer cells, with important implications for applying existing therapies or developing alternate therapeutic approaches.

A deep profile of gene expression across 18 human cancers

Clinically and biologically valuable information may reside untapped in large cancer gene expression data sets. Deep unsupervised learning has the potential to extract this information with unprecedented efficacy but has thus far been hampered by a lack of biological interpretability and robustness. Here, we present DeepProfile, a comprehensive framework that addresses current challenges in applying unsupervised deep learning to gene expression profiles. We use DeepProfile to learn low-dimensional latent spaces for 18 human cancers from 50,211 transcriptomes. DeepProfile outperforms existing dimensionality reduction methods with respect to biological interpretability. Using DeepProfile interpretability methods, we show that genes that are universally important in defining the latent spaces across all cancer types control immune cell activation, while cancer type-specific genes and pathways define molecular disease subtypes. By linking DeepProfile latent variables to secondary tumor characteristics, we discover that tumor mutation burden is closely associated with the expression of cell cycle-related genes. DNA mismatch repair and MHC class II antigen presentation pathway expression, on the other hand, are consistently associated with patient survival. We validate these results through Kaplan-Meier analyses and nominate tumor-associated macrophages as an important source of survival-correlated MHC class II transcripts. Our results illustrate the power of unsupervised deep learning for discovery of novel cancer biology from existing gene expression data.

Ephexin3/ARHGEF5 Together with Cell Migration Signaling Partners within the Tumor Microenvironment Define Prognostic Transcriptional Signatures in Multiple Cancer Types

Cancer cell migration involves a repertoire of signaling proteins that lead cytoskeleton reorganization as a critical step in metastatic dissemination. RhoGEFs are multidomain effectors that integrate signaling inputs to activate the molecular switches that orchestrate actin cytoskeleton reorganization. Ephexins, a group of five RhoGEFs, play oncogenic roles in invasive and metastatic cancer, leading to a mechanistic hypothesis about their function as signaling nodes assembling functional complexes that guide cancer cell migration. To identify clinically significant Ephexin signaling partners, we applied three systematic data mining strategies, based on the screening of essential Ephexins in multiple cancer cell lines and the identification of coexpressed signaling partners in the TCGA cancer patient datasets. Based on the domain architecture of encoded proteins and gene ontology criteria, we selected Ephexin signaling partners with a role in cytoskeletal reorganization and cell migration. We focused on Ephexin3/ARHGEF5, identified as an essential gene in multiple cancer cell types. Based on significant coexpression data and coessentiality, the signaling repertoire that accompanies Ephexin3 corresponded to three groups: pan-cancer, cancer-specific and coessential. To further select the Ephexin3 signaling partners likely to be relevant in clinical settings, we first identified those whose high expression was statistical linked to shorter patient survival. The resulting Ephexin3 transcriptional signatures represent significant accumulated risk, predictive of shorter survival, in 17 cancer types, including PAAD, LUAD, LGG, OSC, AML, KIRC, THYM, BLCA, LIHC and UCEC. The signaling landscape that accompanies Ephexin3 in various cancer types included the tyrosine kinase receptor MET and the tyrosine phosphatase receptor PTPRF, the serine/threonine kinases MARK2 and PAK6, the Rho GTPases RHOD, RHOF and RAC1, and the cytoskeletal regulator DIAHP1. Our findings set the basis to further explore the role of Ephexin3/ARHGEF5 as an essential effector and signaling hub in cancer cell migration.

Polyclonal lymphoid expansion drives paraneoplastic autoimmunity in neuroblastoma

Neuroblastoma is a lethal childhood solid tumor of developing peripheral nerves. Two percent of children with neuroblastoma develop opsoclonus myoclonus ataxia syndrome (OMAS), a paraneoplastic disease characterized by cerebellar and brainstem-directed autoimmunity but typically with outstanding cancer-related outcomes. We compared tumor transcriptomes and tumor-infiltrating T and B cell repertoires from 38 OMAS subjects with neuroblastoma to 26 non-OMAS-associated neuroblastomas. We found greater B and T cell infiltration in OMAS-associated tumors compared to controls and showed that both were polyclonal expansions. Tertiary lymphoid structures (TLSs) were enriched in OMAS-associated tumors. We identified significant enrichment of the major histocompatibility complex (MHC) class II allele HLA-DOB∗01:01 in OMAS patients. OMAS severity scores were associated with the expression of several candidate autoimmune genes. We propose a model in which polyclonal auto-reactive B lymphocytes act as antigen-presenting cells and drive TLS formation, thereby supporting both sustained polyclonal T cell-mediated anti-tumor immunity and paraneoplastic OMAS neuropathology.

ATO Increases ROS Production and Apoptosis of Cells by Enhancing Calpain-Mediated Degradation of the Cancer Survival Protein TG2

Transglutaminase 2 (TG2) is a critical cancer cell survival factor that activates several signalling pathways to foster drug resistance, cancer stem cell survival, metastasis, inflammation, epithelial-mesenchymal transition, and angiogenesis. All-trans retinoic acid (ATRA) and chemotherapy have been the standard treatments for acute promyelocytic leukaemia (APL), but clinical studies have shown that arsenic trioxide (ATO), alone or in combination with ATRA, can improve outcomes. ATO exerts cytotoxic effects in a variety of ways by inducing oxidative stress, genotoxicity, altered signal transduction, and/or epigenetic modification. In the present study, we showed that ATO increased ROS production and apoptosis ratios in ATRA-differentiated NB4 leukaemia cells, and that these responses were enhanced when TG2 was deleted. The combined ATRA + ATO treatment also increased the amount of nuclear factor erythroid 2-related factor 2 (NRF2) transcription factor, an adaptive regulator of the cellular oxidative stress response, and calpain proteolytic activity, resulting in TG2 degradation and the reduced survival of WT leukaemia cells. We further showed that the induced TG2 protein expression was degraded in the MCF-7 epithelial cell line and primary peripheral blood mononuclear cells upon ATO treatment, thereby sensitising these cell types to apoptotic signals.

Transglutaminase 2 associated with PI3K and PTEN in a membrane-bound signalosome platform blunts cell death

Atypically expressed transglutaminase 2 (TG2) has been identified as a poor prognostic factor in a variety of cancers. In this study, we evaluated the contribution of TG2 to the prolonged cell survival of differentiated acute promyelocytic leukaemia (APL) cells in response to the standard treatment with combined retinoic acid (ATRA) and arsenic trioxide (ATO). We report that one advantage of ATRA + ATO treatment compared to ATRA alone diminishes the amount of activated and non-activated CD11b/CD18 and CD11c/CD18 cell surface integrin receptors. These changes suppress ATRA-induced TG2 docking on the cytosolic part of CD18 β2-integrin subunits and reduce cell survival. In addition, TG2 overexpresses and hyperactivates the phosphatidylinositol-3-kinase (PI3K), phospho-AKT S473, and phospho-mTOR S2481 signalling axis. mTORC2 acts as a functional switch between cell survival and death by promoting the full activation of AKT. We show that TG2 presumably triggers the formation of a signalosome platform, hyperactivates downstream mTORC2-AKT signalling, which in turn phosphorylates and inhibits the activity of FOXO3, a key pro-apoptotic transcription factor. In contrast, the absence of TG2 restores basic phospho-mTOR S2481, phospho-AKT S473, PI3K, and PTEN expression and activity, thereby sensitising APL cells to ATO-induced cell death. We conclude, that atypically expressed TG2 may serve as a hub, facilitating signal transduction via signalosome formation by the CD18 subunit with both PI3K hyperactivation and PTEN inactivation through the PI3K-PTEN cycle in ATRA-treated APL cells.

Pan-cancer molecular subtypes of metastasis reveal distinct and evolving transcriptional programs

Molecular mechanisms underlying cancer metastasis span diverse tissues of origin. Here, we synthesize and collate the transcriptomes of patient-derived xenografts and patient tumor metastases, and these data collectively represent 38 studies and over 3,000 patients and 4,000 tumors. We identify four expression-based subtypes of metastasis transcending tumor lineage. The first subtype has extensive copy alterations, higher expression of MYC transcriptional targets and DNA repair genes, and bromodomain inhibitor response association. The second subtype has higher expression of genes involving metabolism and prostaglandin synthesis and regulation. The third subtype has evidence of neuronal differentiation, higher expression of DNA and histone methylation genes and EZH2 transcriptional targets, and BCL2 inhibitor response association. The fourth subtype has higher expression of immune checkpoint and Notch pathway genes. The metastasis subtypes reflect expression differences from paired primaries, with subtype switching being common. These subtypes facilitate understanding of the molecular underpinnings of metastases beyond tissue-oriented domains, with therapeutic implications.

TG2 as a novel breast cancer prognostic marker promotes cell proliferation and glycolysis by activating the MEK/ERK/LDH pathway

BACKGROUND

Breast cancer (BC) is the most common malignant tumor among women worldwide. Tissue transglutaminase 2 (TG2) has been reported as a major player across several types of cancer. However, the effects of TG2 in breast cancer are less known.

METHODS

The expression of TG2 in patients with BC was detected by immunochemistry staining and RT-qPCR. The correlation of TG2 expression and clinicopathological factors or overall survival (OS) was analyzed by Chi-square test, Kaplan-Meier, and Cox-regression analysis. The effects of TG2 on cell proliferation and glycolysis were investigated in vivo and in vitro by gain- and loss-of-function experiments.

RESULT

Both mRNA and protein levels of TG2 were overexpressed in BC tissues and cultured cells. Clinical stage (p = 0.011), molecular subtype (p<0.001) and survival status (p<0.001) were significantly correlated with TG2 expression. Specifically, TG2 expression was positively associated with the clinical stage (r = 0.193, p = 0.005) and OS (r = 0.230, p = 0.001), while negatively associated with molecular subtype (r = - 0.161, p = 0.020). Overexpressed TG2 was a prognostic factor of poor OS by Cox-regression analysis. Gain- and loss-of-function experiments indicated that cell proliferation and glycolysis were regulated by TG2 via the MEK/ERK/LDH pathway. TG2-induced activation of the MEK/ERK/LDH pathway and glycolysis were attenuated by MEK inhibitor U0126.

CONCLUSION

TG2 is overexpressed in BC, which can serve as an independent prognostic factor for OS. TG2 promotes tumor cell proliferation and increases glycolysis associated with the activation of the MEK/ERK/LHD pathway.

The Effect of LL37 Antimicrobial Peptide on FOXE1 and lncRNA PTCSC 2 Genes Expression in Colorectal Cancer (CRC) and Normal Cells

OBJECTIVE

As an innate immune system component, antimicrobial peptides (AMPs) exert various effects, such as anticancer properties. This study aimed to evaluate the LL37 AMP anticancer effect against colorectal cancer (CRC) cells and the expression of FOXE1 and lncRNA PTCSC2 genes.

METHODS

The LL37 AMP was purchased from GenScript USA, Inc. Various CRC cell lines (HCT-116, HT29, WiDr, and SW742) were cultured in the DMEM medium. Various concentrations ranging from (5-400) μg/mL of LL37 AMP were prepared, added to cell cultures, and incubated for (24 and 48) hours. A nontoxic level of 30 µg/mL of LL37 was investigated for FOXE1 and lncRNA PTCSC2 gene expression.

RESULTS

At 24 hours, the (50 and 90) % lethal concentrations of LC50 and LC90, respectively, of LL37 against NCM460 normal cells were (640 and > 640) g/mL. Additionally, these values at 48 hours included (160 and > 640) µg/mL, respectively. After 24 hours of treatment, the LC50 and LC90 of LL37 AMP against CRC cell lines included (20 and 200) µg/mL. The LC50 and LC90 of the LL37 at 48 hours included (20 and 50) µg/mL and at 72 hours. they included (~10 and 40) μg/mL, respectively. FOXE1 but not the PTCSC 2 gene expression was significantly higher in CRC cells than normal cells (NCM460 and HaCaT). The LL37 AMP significantly decreased FOXE1 gene expression by 1.95-fold in CRC cells (p < 0.001).

CONCLUSION

The FOXE1 gene can be considered a biomarker of CRC development. The expression of FOXE1 but not the PTCSC2 gene was significantly affected by the LL37 AMP. The effects of LL37 AMP against CRC cells were time and dose-dependent. Future studies are warranted to verify these effects.

Investigation of Transcript Variant 6 of TPD52L2 as a Prognostic and Predictive Biomarker in Basal-Like MDA-MB-231 and MDA-MB-453 Cell Lines for Breast Cancer

Background

Basal-like breast cancer (BLBC) exhibits worse pathological features than other breast cancer subtypes, and patients diagnosed with BLBC have short disease-free and overall survival times. Thus, the identification of novel biomarkers and therapeutic targets for BLBC is of upmost importance. Although TPD52L2 is upregulated in multiple cancers, little is known about its roles in BLBC.

Methods

RNA levels were analyzed between breast cancer tissues and paired adjacent normal tissues using RNA-seq data from The Cancer Genome Atlas (TCGA). TPD52L2 stable knockdown and inducible knockout cell lines were established using basal-like MDA-MB-231 and MDA-MB-453 cell lines. Cell proliferation assays in vitro and tumor growth analysis in vivo were performed to determine the function of TPD52L2 during BLBC progression. Transwell assays were used to estimate the regulatory effect of TPD52L2 on BLBC cell migration. The expression profile of all tpd52l2 transcripts was analyzed to assess the functional protein isoform. Association of transcript variant 6 (V6) expression with pathological parameters was carried out using the clinical data of the BRCA cohort.

Results

We identified V6 of TPD52L2 as a novel biomarker and regulator of BLBC progression. TPD52L2 is upregulated in BLBCs and associated with patient outcomes. TPD52L2 knockdown suppresses tumor growth, and V6 correlates with cancer-related phenotypes in BLBC. Clinical data further proved that V6 is associated with different pathological features, such as pathological stage and pathological tumor status, and independently predicts patient outcomes and responses to therapies.

Conclusions

Our findings demonstrate that V6 of TPD52L2 is a novel biomarker for BLBC patients. V6 promotes cell proliferation and migration and has marked oncogenic roles in determining the malignant phenotypes of BLBC.

Integrated bioinformatics and statistical approaches to explore molecular biomarkers for breast cancer diagnosis, prognosis and therapies

Integrated bioinformatics and statistical approaches are now playing the vital role in identifying potential molecular biomarkers more accurately in presence of huge number of alternatives for disease diagnosis, prognosis and therapies by reducing time and cost compared to the wet-lab based experimental procedures. Breast cancer (BC) is one of the leading causes of cancer related deaths for women worldwide. Several dry-lab and wet-lab based studies have identified different sets of molecular biomarkers for BC. But they did not compare their results to each other so much either computationally or experimentally. In this study, an attempt was made to propose a set of molecular biomarkers that might be more effective for BC diagnosis, prognosis and therapies, by using the integrated bioinformatics and statistical approaches. At first, we identified 190 differentially expressed genes (DEGs) between BC and control samples by using the statistical LIMMA approach. Then we identified 13 DEGs (AKR1C1, IRF9, OAS1, OAS3, SLCO2A1, NT5E, NQO1, ANGPT1, FN1, ATF6B, HPGD, BCL11A, and TP53INP1) as the key genes (KGs) by protein-protein interaction (PPI) network analysis. Then we investigated the pathogenetic processes of DEGs highlighting KGs by GO terms and KEGG pathway enrichment analysis. Moreover, we disclosed the transcriptional and post-transcriptional regulatory factors of KGs by their interaction network analysis with the transcription factors (TFs) and micro-RNAs. Both supervised and unsupervised learning's including multivariate survival analysis results confirmed the strong prognostic power of the proposed KGs. Finally, we suggested KGs-guided computationally more effective seven candidate drugs (NVP-BHG712, Nilotinib, GSK2126458, YM201636, TG-02, CX-5461, AP-24534) compared to other published drugs by cross-validation with the state-of-the-art alternatives top-ranked independent receptor proteins. Thus, our findings might be played a vital role in breast cancer diagnosis, prognosis and therapies.

Tumor Purity in Preclinical Mouse Tumor Models

Tumor biology is determined not only by immortal cancer cells but also by the tumor microenvironment consisting of noncancerous cells and extracellular matrix, together they dictate the pathogenesis and response to treatments. Tumor purity is the proportion of cancer cells in a tumor. It is a fundamental property of cancer and is associated with many clinical features and outcomes. Here we report the first systematic study of tumor purity in patient-derived xenograft (PDX) and syngeneic tumor models using next-generation sequencing data from >9,000 tumors. We found that tumor purity in PDX models is cancer specific and mimics patient tumors, with variation in stromal content and immune infiltration influenced by immune systems of host mice. After the initial engraftment, human stroma in a PDX tumor is quickly replaced by mouse stroma, and tumor purity then stays stable in subsequent transplantations and increases only slightly by passage. Similarly, in syngeneic mouse cancer cell line models, tumor purity also turns out to be an intrinsic property with model and cancer specificities. Computational and pathology analysis confirmed the impact on tumor purity by the diverse stromal and immune profiles. Our study deepens the understanding of mouse tumor models, which will enable their better and novel uses in developing cancer therapeutics, especially ones targeting tumor microenvironment.

Significance

PDX models are an ideal experimental system to study tumor purity because of its distinct separation of human tumor cells and mouse stromal and immune cells. This study provides a comprehensive view of tumor purity in 27 cancers in PDX models. It also investigates tumor purity in 19 syngeneic models based on unambiguously identified somatic mutations. It will facilitate tumor microenvironment research and drug development in mouse tumor models.

Proteogenomic analysis of pancreatic cancer subtypes

Pancreatic cancer remains a significant public health problem with an ever-rising incidence of disease. Cancers of the pancreas are characterised by various molecular aberrations, including changes in the proteomics and genomics landscape of the tumour cells. Therefore, there is a need to identify the proteomic landscape of pancreatic cancer and the specific genomic and molecular alterations associated with disease subtypes. Here, we carry out an integrative bioinformatics analysis of The Cancer Genome Atlas dataset, including proteomics and whole-exome sequencing data collected from pancreatic cancer patients. We apply unsupervised clustering on the proteomics dataset to reveal the two distinct subtypes of pancreatic cancer. Using functional and pathway analysis based on the proteomics data, we demonstrate the different molecular processes and signalling aberrations of the pancreatic cancer subtypes. In addition, we explore the clinical characteristics of these subtypes to show differences in disease outcome. Using datasets of mutations and copy number alterations, we show that various signalling pathways previously associated with pancreatic cancer are altered among both subtypes of pancreatic tumours, including the Wnt pathway, Notch pathway and PI3K-mTOR pathways. Altogether, we reveal the proteogenomic landscape of pancreatic cancer subtypes and the altered molecular processes that can be leveraged to devise more effective treatments.

Evaluation of Somatic Mutations in Solid Metastatic Pan-Cancer Patients

Metastasis continues to be the primary cause of all cancer-related deaths despite the recent advancements in cancer treatments. To evaluate the role of mutations in overall survival (OS) and treatment outcomes, we analyzed 957 metastatic patients with seven major cancer types who had available molecular testing results with a FoundationOne CDx® panel. The most prevalent genes with somatic mutations were TP53, KRAS, APC, and LRP1B. In this analysis, these genes had mutation frequencies higher than in publicly available datasets. We identified that the somatic mutations were seven mutually exclusive gene pairs and an additional fifty-two co-occurring gene pairs. Mutations in the mutually exclusive gene pair APC and CDKN2A showed an opposite effect on the overall survival. However, patients with CDKN2A mutations showed significantly shorter OS (HR: 1.72, 95% CI: 1.34-2.21, p < 0.001) after adjusting for cancer type, age at diagnosis, and sex. Five-year post metastatic diagnosis survival analysis showed a significant improvement in OS (median survival 28 and 43 months in pre-2015 and post-2015 metastatic diagnosis, respectively, p = 0.00021) based on the year of metastatic diagnosis. Although the use of targeted therapies after metastatic diagnosis prolonged OS, the benefit was not statistically significant. However, longer five-year progression-free survival (PFS) was significantly associated with targeted therapy use (median 10.9 months (CI: 9.7-11.9 months) compared to 9.1 months (CI: 8.1-10.1 months) for non-targeted therapy, respectively, p = 0.0029). Our results provide a clinically relevant overview of the complex molecular landscape and survival mechanisms in metastatic solid cancers.

Deciphering molecular mechanisms of metastasis: novel insights into targets and therapeutics

BACKGROUND

The transition of a primary tumour to metastatic progression is driven by dynamic molecular changes, including genetic and epigenetic alterations. The metastatic cascade involves bidirectional interactions among extracellular and intracellular components leading to disintegration of cellular junctions, cytoskeleton reorganization and epithelial to mesenchymal transition. These events promote metastasis by reprogramming the primary cancer cell's molecular framework, enabling them to cause local invasion, anchorage-independent survival, cell death and immune resistance, extravasation and colonization of distant organs. Metastasis follows a site-specific pattern that is still poorly understood at the molecular level. Although various drugs have been tested clinically across different metastatic cancer types, it has remained difficult to develop efficacious therapeutics due to complex molecular layers involved in metastasis as well as experimental limitations.

CONCLUSIONS

In this review, a systemic evaluation of the molecular mechanisms of metastasis is outlined and the potential molecular components and their status as therapeutic targets and the associated pre-clinical and clinical agents available or under investigations are discussed. Integrative methods like pan-cancer data analysis, which can provide clinical insights into both targets and treatment decisions and help in the identification of crucial components driving metastasis such as mutational profiles, gene signatures, associated pathways, site specificities and disease-gene phenotypes, are discussed. A multi-level data integration of the metastasis signatures across multiple primary and metastatic cancer types may facilitate the development of precision medicine and open up new opportunities for future therapies.

Targeting neddylation E2s: a novel therapeutic strategy in cancer

Ubiquitin-conjugating enzyme E2 M (UBE2M) and ubiquitin-conjugating enzyme E2 F (UBE2F) are the two NEDD8-conjugating enzymes of the neddylation pathway that take part in posttranslational modification and change the activity of target proteins. The activity of E2 enzymes requires both a 26-residue N-terminal docking peptide and a conserved E2 catalytic core domain, which is the basis for the transfer of neural precursor cell-expressed developmentally downregulated 8 (NEDD8). By recruiting E3 ligases and targeting cullin and non-cullin substrates, UBE2M and UBE2F play diverse biological roles. Currently, there are several inhibitors that target the UBE2M-defective in cullin neddylation protein 1 (DCN1) interaction to treat cancer. As described above, this review provides insights into the mechanism of UBE2M and UBE2F and emphasizes these two E2 enzymes as appealing therapeutic targets for the treatment of cancers.

Genome-wide DNA methylation and RNA expression differences correlate with invasiveness in melanoma cell lines

Aims & objectives: The aim of this study was to investigate the role of DNA methylation in invasiveness in melanoma cells. Materials & methods: The authors carried out genome-wide transcriptome (RNA sequencing) and reduced representation bisulfite sequencing methylome profiling between noninvasive (n = 4) and invasive melanoma cell lines (n = 5). Results: The integration of differentially expressed genes and differentially methylated fragments (DMFs) identified 12 DMFs (two in AVPI1, one in HMG20B, two in BCL3, one in NTSR1, one in SYNJ2, one in ROBO2 and four in HORMAD2) that overlapped with either differentially expressed genes (eight DMFs and six genes) or cis-targets of lncRNAs (five DMFs associated with cis-targets and four differentially expressed lncRNAs). Conclusions: DNA methylation changes are associated with a number of transcriptional differences observed in noninvasive and invasive phenotypes in melanoma.

Treatment of Brain Metastases of Non-Small Cell Lung Carcinoma

Lung cancer is one of the most common malignant neoplasms. As a result of the disease's progression, patients may develop metastases to the central nervous system. The prognosis in this location is unfavorable; untreated metastatic lesions may lead to death within one to two months. Existing therapies-neurosurgery and radiation therapy-do not improve the prognosis for every patient. The discovery of Epidermal Growth Factor Receptor (EGFR)-activating mutations and Anaplastic Lymphoma Kinase (ALK) rearrangements in patients with non-small cell lung adenocarcinoma has allowed for the introduction of small-molecule tyrosine kinase inhibitors to the treatment of advanced-stage patients. The Epidermal Growth Factor Receptor (EGFR) is a transmembrane protein with tyrosine kinase-dependent activity. EGFR is present in membranes of all epithelial cells. In physiological conditions, it plays an important role in the process of cell growth and proliferation. Binding the ligand to the EGFR causes its dimerization and the activation of the intracellular signaling cascade. Signal transduction involves the activation of MAPK, AKT, and JNK, resulting in DNA synthesis and cell proliferation. In cancer cells, binding the ligand to the EGFR also leads to its dimerization and transduction of the signal to the cell interior. It has been demonstrated that activating mutations in the gene for EGFR-exon19 (deletion), L858R point mutation in exon 21, and mutation in exon 20 results in cancer cell proliferation. Continuous stimulation of the receptor inhibits apoptosis, stimulates invasion, intensifies angiogenesis, and facilitates the formation of distant metastases. As a consequence, the cancer progresses. These activating gene mutations for the EGFR are present in 10-20% of lung adenocarcinomas. Approximately 3-7% of patients with lung adenocarcinoma have the echinoderm microtubule-associated protein-like 4 (EML4)/ALK fusion gene. The fusion of the two genes EML4 and ALK results in a fusion gene that activates the intracellular signaling pathway, stimulates the proliferation of tumor cells, and inhibits apoptosis. A new group of drugs-small-molecule tyrosine kinase inhibitors-has been developed; the first generation includes gefitinib and erlotinib and the ALK inhibitor crizotinib. These drugs reversibly block the EGFR by stopping the signal transmission to the cell. The second-generation tyrosine kinase inhibitor (TKI) afatinib or ALK inhibitor alectinib block the receptor irreversibly. Clinical trials with TKI in patients with non-small cell lung adenocarcinoma with central nervous system (CNS) metastases have shown prolonged, progression-free survival, a high percentage of objective responses, and improved quality of life. Resistance to treatment with this group of drugs emerging during TKI therapy is the basis for the detection of resistance mutations. The T790M mutation, present in exon 20 of the EGFR gene, is detected in patients treated with first- and second-generation TKI and is overcome by Osimertinib, a third-generation TKI. The I117N resistance mutation in patients with the ALK mutation treated with alectinib is overcome by ceritinib. In this way, sequential therapy ensures the continuity of treatment. In patients with CNS metastases, attempts are made to simultaneously administer radiation therapy and tyrosine kinase inhibitors. Patients with lung adenocarcinoma with CNS metastases, without activating EGFR mutation and without ALK rearrangement, benefit from immunotherapy. This therapeutic option blocks the PD-1 receptor on the surface of T or B lymphocytes or PD-L1 located on cancer cells with an applicable antibody. Based on clinical trials, pembrolizumab and all antibodies are included in the treatment of non-small cell lung carcinoma with CNS metastases.

Identifying the key genes and microRNAs in prostate cancer bone metastasis by bioinformatics analysis

Prostate adenocarcinoma (PCa) is the most common cause of death due to malignancy among men, and bone metastasis is the leading cause of mortality in patients with PCa. Therefore, identifying the causes and molecular mechanism of bone metastasis is important for early detection, diagnosis and personalized therapy. In this study, we systematically analyzed molecular correlates of bone metastasis by bioinformatics analysis. A total of 12 differentially expressed microRNAs (miRNAs) and 102 differentially expressed genes were identified. Five miRNAs had prognostic significance in biochemical recurrence‐free survival (miR‐636, miR‐491‐5p, miR‐199b‐5p, miR‐199b‐3p, miR‐28‐3p). The differentially expressed genes were significantly enriched in extracellular matrix, cell‐substrate adhesion, collagen and integrin. Seven hub genes (VCAN, COL3A1, COL1A1, APOE, COL1A2, SDC1, THY1) with worse biochemical recurrence‐free survival and one hub gene (MMP9) with worse overall survival were detected. miR‐636, a novel oncogene, was found to be up‐regulated in bone metastatic PCa tissues and also predominately up‐regulated in human PCa cell lines. miR‐636 promoted cellular invasion and migration, and may promote bone metastasis via targeting MBNL2, TNS1 and STAB1. In conclusion, we have successfully defined molecular signatures of bone metastasis in PCa.

Advancing the Role of Gamma-Tocotrienol as Proteasomes Inhibitor: A Quantitative Proteomic Analysis of MDA-MB-231 Human Breast Cancer Cells

Tocotrienol, an analogue of vitamin E has been known for its numerous health benefits and anti-cancer effects. Of the four isoforms of tocotrienols, gamma-tocotrienol (γT3) has been frequently reported for their superior anti-tumorigenic activity in both in vitro and in vivo studies, when compared to its counterparts. In this study, the effect of γT3 treatment in the cytoplasmic and nuclear fraction of MDA-MB-231 human breast cancer cells were assessed using the label-free quantitative proteomics analysis. The cytoplasmic proteome results revealed the ability of γT3 to inhibit a group of proteasome proteins such as PSMA, PSMB, PSMD, and PSME. The inhibition of proteasome proteins is known to induce apoptosis in cancer cells. As such, the findings from this study suggest γT3 as a potential proteasome inhibitor that can overcome deficiencies in growth-inhibitory or pro-apoptotic molecules in breast cancer cells. The nuclear proteome results revealed the involvement of important nuclear protein complexes which hardwire the anti-tumorigenesis mechanism in breast cancer following γT3 treatment. In conclusion, this study uncovered the advancing roles of γT3 as potential proteasomes inhibitor that can be used for the treatment of breast cancer.

Mutational concordance between primary and metastatic melanoma: a next-generation sequencing approach

Background

Cutaneous malignant melanoma (CMM) is one of the most common skin cancers worldwide. Limited information is available in the current scientific literature on the concordance of genetic alterations between primary and metastatic CMM. In the present study, we performed next-generation sequencing (NGS) analysis of the main genes participating in melanoma pathogenesis and progression, among paired primary and metastatic lesions of CMM patients, with the aim to evaluate levels of discrepancies in mutational patterns.

Methods

Paraffin-embedded tumor tissues of the paired lesions were retrieved from the archives of the institutions participating in the study. NGS was performed using a specific multiple-gene panel constructed by the Italian Melanoma Intergroup (IMI) to explore the mutational status of selected regions (343 amplicons; amplicon range: 125–175 bp; coverage 100%) within the main 25 genes involved in CMM pathogenesis; sequencing was performed with the Ion Torrent PGM System.

Results

A discovery cohort encompassing 30 cases, and a validation cohort including eleven Sardinian patients with tissue availability from both the primary and metachronous metastatic lesions were identified; the global number of analyzed tissue specimens was 90. A total of 829 genetic non-synonymous variants were detected: 101 (12.2%) were pathogenic/likely pathogenic, 131 (15.8%) were benign/likely benign, and the remaining 597 (72%) were uncertain/unknown significance variants. Considering the global cohort, the consistency in pathogenic/pathogenic like mutations was 76%. Consistency for BRAF and NRAS mutations was 95.2% and 85.7% respectively, without statistically significant differences between the discovery and validation cohort.

Conclusions

Our study showed a high level of concordance in mutational patterns between primary and metastatic CMM, especially when pathogenic mutations in driver genes were considered.

Immune Microenvironment of Brain Metastases-Are Microglia and Other Brain Macrophages Little Helpers?

Brain metastases are common intracranial neoplasms and their frequency increases with prolonged survival of cancer patients. New pharmaceuticals targeting oncogenic kinases and immune checkpoint inhibitors augment both overall and progression-free survival in patients with brain metastases, but are not fully successful in reducing metastatic burden and still a majority of oncologic patients die due to dissemination of the disease. Despite therapy advancements, median survival of patients with brain metastases is several months, although it may vary in different types or subtypes of cancer. Contribution of the innate immune system to cancer progression is well established. Tumor-associated macrophages (TAMs), instead of launching antitumor responses, promote extracellular matrix degradation, secrete immunosuppressive cytokines, promote neoangiogenesis and tumor growth. While their roles as pro-tumorigenic cells facilitating tissue remodeling, invasion and metastasis is well documented, much less is known about the immune microenvironment of brain metastases and roles of specific immune cells in those processes. The central nervous system (CNS) is armed in resident myeloid cells: microglia and perivascular macrophages which colonize CNS in early development and maintain homeostasis in brain parenchyma and at brain-blood vessels interfaces. In this study we discuss available data on the immune composition of most common brain metastases, focusing on interactions between metastatic cancer cells and microglia, perivascular and meningeal macrophages. Cancer cells ‘highjack’ several CNS protective mechanisms and may employ microglia and CNS-border associated macrophages into helping cancer cells to colonize a pre-metastatic niche. We describe emerging molecular insights into mechanisms governing communication between microglia and metastatic cancer cells that culminate in activation of CNS resident microglia and trafficking of monocytic cells from the periphery. We present mechanisms controlling those processes in brain metastases and hypothesize on potential therapeutic approaches. In summary, microglia and non-parenchymal brain macrophages are involved in multiple stages of a metastatic disease and, unlike tumor cells, are genetically stable and predictable, which makes them an attractive target for anticancer therapies.

A cross-cancer metastasis signature in the microRNA-mRNA axis of paired tissue samples

In the progression of cancer, cells acquire genetic mutations that cause uncontrolled growth. Over time, the primary tumour may undergo additional mutations that allow for the cancerous cells to spread throughout the body as metastases. Since metastatic development typically results in markedly worse patient outcomes, research into the identity and function of metastasis-associated biomarkers could eventually translate into clinical diagnostics or novel therapeutics. Although the general processes underpinning metastatic progression are understood, no clear cross-cancer biomarker profile has emerged. However, the literature suggests that some microRNAs (miRNAs) may play an important role in the metastatic progression of several cancer types. Using a subset of The Cancer Genome Atlas (TCGA) data, we performed an integrated analysis of mRNA and miRNA expression with paired metastatic and primary tumour samples to interrogate how the miRNA-mRNA regulatory axis influences metastatic progression. From this, we successfully built mRNA- and miRNA-specific classifiers that can discriminate pairs of metastatic and primary samples across 11 cancer types. In addition, we identified a number of miRNAs whose metastasis-associated dysregulation could predict mRNA metastasis-associated dysregulation. Among the most predictive miRNAs, we found several previously implicated in cancer progression, including miR-301b, miR-1296, and miR-423. Taken together, our results suggest that metastatic samples have a common cross-cancer signature when compared with their primary tumour pair, and that these miRNA biomarkers can be used to predict metastatic status as well as mRNA expression.

The Homeobox gene, HOXB13, Regulates a Mitotic Protein-Kinase Interaction Network in Metastatic Prostate Cancers

HOXB13, a homeodomain transcription factor, is linked to recurrence following radical prostatectomy. While HOXB13 regulates Androgen Receptor (AR) functions in a context dependent manner, its critical effectors in prostate cancer (PC) metastasis remain largely unknown. To identify HOXB13 transcriptional targets in metastatic PCs, we performed integrative bioinformatics analysis of differentially expressed genes (DEGs) in the proximity of the human prostate tumor-specific AR binding sites. Unsupervised Principal Component Analysis (PCA) led to a focused core HOXB13 target gene-set referred to as HOTPAM9 (HOXB13 Targets separating Primary And Metastatic PCs). HOTPAM9 comprised 7 mitotic kinase genes overexpressed in metastatic PCs, TRPM8, and the heat shock protein HSPB8, whose levels were significantly lower in metastatic PCs compared to the primary disease. The expression of a two-gene set, CIT and HSPB8 with an overall balanced accuracy of 98.8% and a threshold value of 0.2347, was sufficient to classify metastasis. HSPB8 mRNA expression was significantly increased following HOXB13 depletion in multiple metastatic CRPC models. Increased expression of HSPB8 by the microtubule inhibitor Colchicine or by exogenous means suppressed migration of mCRPC cells. Collectively, our results indicate that HOXB13 promotes metastasis of PCs by coordinated regulation of mitotic kinases and blockade of a putative tumor suppressor gene.